Identification of Optimal Reference Genes for Normalization of qPCR Analysis during Pepper Fruit Development.

Due to its high sensitivity and reproducibility, quantitative real-time PCR (qPCR) is practiced as a useful research tool for targeted gene expression analysis. For qPCR operations, the normalization with suitable reference genes (RGs) is a crucial step that eventually determines the reliability of the obtained results. Although pepper is considered an ideal model plant for the study of non-climacteric fruit development, at present no specific RG have been developed or validated for the qPCR analyses of pepper fruit. Therefore, this study aimed to identify stably expressed genes for their potential use as RGs in pepper fruit studies. Initially, a total of 35 putative RGs were selected by mining the pepper transcriptome data sets derived from the PGP (Pepper Genome Platform) and PGD (Pepper Genome Database). Their expression stabilities were further measured in a set of pepper ( L. var. 007e) fruit samples, which represented four different fruit developmental stages (IM: Immature; MG: Mature green; B: Break; MR: Mature red) using the qPCR analysis. Then, based on the qPCR results, three different statistical algorithms, namely geNorm, Normfinder, and boxplot, were chosen to evaluate the expression stabilities of these putative RGs. It should be noted that nine genes were proven to be qualified as RGs during pepper fruit development, namely (CA00g79660); (CA06g02180); (CA06g05650); (Capana12g002666); (Capana10g001439); (Capana05g000680); (Capana01g002973); (Capana11g000123); (Capana04g002411); and (Capana08g001826). Further analysis based on geNorm suggested that the application of the two most stably expressed genes ( and ) would provide optimal transcript normalization in the qPCR experiments. Therefore, a new and comprehensive strategy for the identification of optimal RGs was developed. This strategy allowed for the effective normalization of the qPCR analysis of the pepper fruit development at the whole pepper genome level. This study not only explored the optimal RGs specific for studying pepper fruit development, but also introduced a referable strategy of RG mining which could potentially be implicated in other plant species.